z-class {FLEDA} | R Documentation |
This class encapsulates results of a z
method.
Objects of this classe should be created with a call to the contructor function z(object, agerng, ...)
, where object
must be an object of class "FLQuant"
, agerng
is the age range of fully expoited ages and ...
can be used to pass trim
arguments to the creator funtion.
"FLQuant"
."FLQuant"
."FLQuant"
."numeric"
.signature(object = "z")
: Display object briefly.signature(object = "z")
: Displays the average total mortality computed by age and cohort.signature(object = "z")
: Tests the similarities between the estimates by year and by cohort.signature(object = "z")
: Lattice xyplot
method.
Considering C_{ay}, the catch in numbers at age a=1,...,A per year y=1,...,Y, obtained e.g. from the catch.n slot of a "FLStock"
object, the computation of z
is performed by year Z_{y}, by age Z_{a} and by cohorts Z_{c}, for a defined age range (agerng
):
Consider a:a in agerng, n=#a and
L_{ay}=log{frac{C_{ay}}{C_{a+1,y+1}}}
than
Z_{y}=frac{sum_{a}{L_{ay}}}{n}
Z_{a}=frac{sum_{y}{L_{ay}}}{Y}
Z_{c}=frac{sum_{c}{L_{ay}}}{n}
If agerng
is not provided, the method will try to guess this argument by finding the ages that have less than 10% negative logs along the time series. This procedure may have unexpected side effects !
FLQuant-class
, trim
, logr-class
data(ple4) # compute Z ple4z <- z(catch.n(ple4), agerng=3:6) # tune plot ttl <- list("Total mortality (Z) for Plaice in IV", cex=1) xttl <- list(cex=0.8) yttl <- list("Mean Z", cex=0.8) # plot z by age along years xyplot(data~year, data=ple4z@zy, type="l", main=ttl, ylab=yttl, xlab=xttl) # plot z by age along ages xyplot(data~age, data=ple4z@za, type="l", main=ttl, ylab=yttl, xlab=xttl) # plot z by cohort along years xyplot(data~cohort, data=ple4z@zc, type="l", main=ttl, ylab=yttl, xlab=xttl)